Many common diseases show familial aggregation and are therefore suspected to be at least partially genetically determined. Geneticists have developed and applied a variety of mathematical techniques for analyzing the familial patterns of occurrence of these diseases in an attempt to clarify the nature of the genetic and environmental contributions to disease susceptibility. However, the extent to which these techniques are capable of sorting out the relative roles of genetic and environmental factors is still not known. The aim of this project is to initiate an evaluation of some of the more commonly used methods for the genetic analysis of common diseases, in particular, segregation analysis. A package of computer programs will be developed and used to generate pedigrees whose relevant genetic, demographic and environmental characteristics are completely specified. This package will include programs (1) to generate nuclear families, larger pedigrees, and entire populations; (2) to assign multi-locus genotypes; (3) to assign environments; (4) to determine phenotypes for individuals on the basis of their genotypes and environments; (5) to ascertain probands and assemble data sets for genetic analysis; and (6) to enter data on magnetic tape in LIPED format. The data sets will be submitted to a number of research groups who will analyze them blind, i.e., without knowledge of the underlying genetic/environmental model. Investigators will be asked first to determine the most likely mode of inheritance, then to estimate parameters, and finally to provide numerical values for the relative likelihoods of various modes of inheritance. The conclusions of the various groups will be discussed and compared at a series of yearly workshops, to be held in conjunction with the meetings of the American Society of Human Genetics. By the end of the third year of this project, we will have developed a set of exportable simulation programs that can be used by other investigators who want to do their own evaluations of methods of genetic analysis.